Perceptually Guided Automatic Parameter Optimization for Interactive Visualization

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dc.contributor.authorOpitz, Danielen_US
dc.contributor.authorZirr, Tobiasen_US
dc.contributor.authorDachsbacher, Carstenen_US
dc.contributor.authorTessari, Lorenzoen_US
dc.contributor.editorGuthe, Michaelen_US
dc.contributor.editorGrosch, Thorstenen_US
dc.date.accessioned2023-09-25T11:37:19Z
dc.date.available2023-09-25T11:37:19Z
dc.date.issued2023
dc.description.abstractWe propose a new reference-free method for automatically optimizing the parameters of visualization techniques such that the perception of visual structures is improved. Manual tuning may require domain knowledge not only in the field of the analyzed data, but also deep knowledge of the visualization techniques, and thus often becomes challenging as the number of parameters that impact the result grows. To avoid this laborious and difficult task, we first derive an image metric that models the loss of perceived information in the processing of a displayed image by a human observer; good visualization parameters minimize this metric. Our model is loosely based on quantitative studies in the fields of perception and biology covering visual masking, photo receptor sensitivity, and local adaptation. We then pair our metric with a generic parameter tuning algorithm to arrive at an automatic optimization method that is oblivious to the concrete relationship between parameter sets and visualization. We demonstrate our method for several volume visualization techniques, where visual clutter, visibility of features, and illumination are often hard to balance. Since the metric can be efficiently computed using image transformations, it can be applied to many visualization techniques and problem settings in a unified manner, including continuous optimization during interactive visual exploration. We also evaluate the effectiveness of our approach in a user study that validates the improved perception of visual features in results optimized using our model of perception.en_US
dc.description.sectionheadersImage Visualization and Analysis
dc.description.seriesinformationVision, Modeling, and Visualization
dc.identifier.doi10.2312/vmv.20231228
dc.identifier.isbn978-3-03868-232-5
dc.identifier.pages71-80
dc.identifier.pages10 pages
dc.identifier.urihttps://doi.org/10.2312/vmv.20231228
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/vmv20231228
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titlePerceptually Guided Automatic Parameter Optimization for Interactive Visualizationen_US
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